Accurate state of charge (SOC) constitutes the basis for reliable operations of lithium-ion
batteries. The deep learning technique, a game changer in many fields, has recently …

Early detection of faulty patterns and timely scheduling of maintenance events can minimize
risk to the underlying processes and increase a system's lifespan, reliability, and availability …

Remaining useful life (RUL) prediction as the key technique of prognostics and health
management (PHM) has been extensively investigated. The application of data-driven …

Due to the neglect of prior characteristics and the lack of explicit constraints on fault
knowledge, conventional intelligent diagnosis methods suffer from great hardships in …

Representation learning-based remaining useful life (RUL) prediction plays a crucial role in
improving the security and reducing the maintenance cost of complex systems. Despite the …

Deep learning-based methods play an increasingly significant role in prognostic and health
management, enabling accurate and rapid estimation of the remaining useful life (RUL) …

Remaining useful life (RUL) prediction is of vital significance in prognostics health
management tasks. Due to powerful learning capabilities, deep learning methods …

In actual industrial scenarios, the centralized learning paradigm for remaining useful life
(RUL) prediction of rotating machineries usually suffers from several bottlenecks. Firstly, the …

Rolling bearings are key components in industrial machinery, and their remaining useful life
(RUL) prediction plays a prominent part in machine safety and maintenance. Bidirectional …

The rise of Internet of Things (IoT) technology has moved the digital world in a new direction
and is considered the third wave of the information industry. To meet the current growing …